Determination of pesticides and their metabolites in processed cereal samples.

Fifteen pesticides including some of their metabolites (disulfoton sulfoxide, ethoprophos, cadusafos, dimethoate, terbufos, disulfoton, chlorpyrifos-methyl, malaoxon, fenitrothion, pirimiphos-methyl, malathion, chlorpyrifos, terbufos sulfone, disulfoton sulfone and fensulfothion) were analysed in milled toasted wheat and maize as well as in wheat flour and baby cereals. The QuEChERS (quick, easy, cheap, effective, rugged and safe) methodology was used and its dispersive solid-phase extraction procedure was optimised by means of an experimental design with the aim of reducing the amount of co-extracted lipids and obtaining a clean extract. Gas chromatography with nitrogen phosphorus detection were used as the separation and detection techniques, respectively. The method was validated in terms of selectivity, recoveries, calibration, precision and accuracy as well as matrix effects. Limits of detection were between 0.07 and 34.8 µg kg(-1) with recoveries in the range of 71-110% (relative standard deviations were below 9%). A total of 40 samples of different origin were analysed. Residues of pirimiphos-methyl were found in six of the samples at concentrations in the range 0.08-0.47 mg kg(-1), which were below the MRLs established for this pesticide in cereal grains. Tandem mass spectrometry confirmation was also carried out in order to identify unequivocally the presence of this pesticide.

Evaluation of a modified QuEChERS method for the extraction of pesticides from agricultural, ornamental and forestal soils.

A modified version of the QuEChERS method has been developed for the determination of a group of ten organophosphorus pesticides (i.e. ethoprofos, dimethoate, diazinon, malaoxon, chlorpyrifos-methyl, fenitrothion, malathion, chlorpyrifos, fenamiphos and phosmet) and one thiadiazine pesticide (buprofezin) in three different types of soils (forestal, ornamental and agricultural). The method was validated through linearity, recovery, precision and accuracy studies, and also by carrying out a matrix-matched calibration for the three soils owing to the existence of a strong matrix effect. Acceptable recovery values were obtained (between 45 and 96%) for all the pesticides and soils, except for malathion and malaoxon in forestal and ornamental soils, from which they could not be quantitatively extracted. Limits of detection of the whole method ranged between 0.48 and 7.78 ng/g. The method was finally applied to the determination of chlorpyrifos concentration in a treated soil for cultivation of potatoes.

Evaluation of multi-walled carbon nanotubes as solid-phase extraction adsorbents of pesticides from agricultural, ornamental and forestal soils.

A new, simple and cost-effective method based on the use of multi-walled carbon nanotubes (MWCNTs) as solid-phase extraction stationary phases is proposed for the determination of a group of seven organophosphorus pesticides (i.e. ethoprophos, diazinon, chlorpyriphos-methyl, fenitrothion, malathion, chlorpyriphos and phosmet) and one thiadiazine (buprofezin) in different kinds of soil samples (forestal, ornamental and agricultural) using gas chromatography with nitrogen phosphorus detection. Soils were first ultrasound extracted with 10 mL 1:1 methanol/acetonitrile (v/v) and the evaporated extract redissolved in 20 mL water (pH 6.0) was passed through 100 mg of MWCNTs of 10-15 nm o.d., 2-6 nm i.d. and 0.1-10 microm length. Elution was carried out with 20 mL dichloromethane. The method was validated in terms of linearity, precision, recovery, accuracy and selectivity. Matrix-matched calibration was carried out for each type of soil since statistical differences between the calibration curves constructed in pure solvent and in the reconstituted soil extract were found for most of the pesticides under study. Recovery values of spiked samples ranged between 54 and 91% for the three types of soils (limits of detection (LODs) between 2.97 and 9.49 ngg(-1)), except for chlorpyrifos, chlorpyrifos-methyl and buprofezin which ranged between 12 and 54% (LODs between 3.14 and 72.4 ngg(-1)), which are the pesticides with the highest soil organic carbon sorption coefficient (K(OC)) values. Using a one-sample test (Student's t-test) with fortified samples at two concentration levels in each type of soil, no significant differences were observed between the real and the experimental values (accuracy percentages ranged between 87 and 117%). It is the first time that the adsorptive potential of MWCNTs for the extraction of organophosphorus pesticides from soils is investigated.

Pesticide analysis by capillary electrophoresis.

In this work, a critical and updated revision of the current situation of the analysis of pesticides by Capillary Electrophoresis (CE) is presented. The review has been written in two main sections. The first one presents a thorough revision of the various offline and on-line sample preconcentration procedures that have been used in conjunction with CE to analyze these compounds. The second part reviews the various detection strategies (i.e., UV, LIF, MS, and electrochemical) and CE modes that have been applied to the analysis of pesticides. Future trends that can be expected from this hot research area are also discussed.

Content of aliphatic hydrocarbons in limpets as a new way for classification of species using artificial neural networks.

It is demonstrated that biological species like limpets can be classified according to their level of n-alkanes when artificial neural networks are applied. Marine intertidal and subtidal limpets of the Canary Islands (Spain), Patella piperata, Patella candei crenata and Patella ulyssiponensis aspera were selected as bioindicator organisms. Samples were collected at four stations on the coasts of Fuerteventura. Concentration of n-alkanes in the soft tissues of the limpets has been determined by gas chromatography. Data were treated with artificial neural networks (ANNs) and it was found that using suitable architecture of a supervised artificial neural network, the limpets can be successfully distinguished (classified) up to 98%.